Scalable and Energy-Efficient Multimedia Content Sharing over New Generation Computing and Communication Platforms

通过新一代计算和通信平台实现可扩展且节能的多媒体内容共享

基本信息

  • 批准号:
    RGPIN-2014-04765
  • 负责人:
  • 金额:
    $ 3.35万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2017
  • 资助国家:
    加拿大
  • 起止时间:
    2017-01-01 至 2018-12-31
  • 项目状态:
    已结题

项目摘要

In the past decade, we have witnessed the fast evolution toward a new generation of social, mobile and cloud computing for networked multimedia processing and sharing. Today, high-definition videos and even 3D/multiview videos can be readily captured and browsed by personal computing devices, and conveniently processed and stored with remote cloud resources. The users are now actively engaged to be part of a social ecosystem, rather than passively receiving media content. The revolution is being driven further by the deep penetration of 3G/4G wireless networks and smart mobile devices that are seamlessly integrated with online social networking and media sharing services. Despite the increasingly abundant bandwidth and computation resources, the ever increasing data volume of user generated media content and the boundless coverage of socialized sharing have presented unprecedented challenges to both content and network service providers. The highly diversified media content types, origins, distribution channels further impose complex interactions among the different components in a networked sharing system. We thus ask the following critical question: how can the massive media content be efficiently generated and distributed among massive clients with the latest social, mobile, and cloud computing and communication platforms? Besides scalability, energy has become a critical concern with these new generation computation and communication platforms, too. On the mobile terminal side, the highly constrained battery reservoir has long been a bottleneck in service time between recharges; on the cloud side, the datacenters are known to be power-hungry. The computation- and bandwidth-intensive multimedia services that extensively use CPU, GPU, storage, and network resources certainly make the situation worse. Is has been predicted that multimedia energy consumption is rising at 16% per year, accounting for half of the annual operating expenditure of these services. To achieve the ultimate goals of scalable and energy-efficient media sharing for anyone, anytime, and anywhere, technology advances in various aspects need to be re-examined and jointly optimized under a coherent framework. In this proposed long-term research, we will address the above challenges in the latest computing and communication environments. We will focus not only on the optimization of individual components, ranging from media content generation, network and cloud resource allocation, social media propagation, to energy-efficient media computation and communications in cloud and in local devices, but also on their interactions that pose additional problems to designers. A thorough understanding of the modules in this complex system as well as their interactions will facilitate the development of such essential services as social media, IPTV, movie-on-demand, video conferencing, and interactive online gaming in the emerging digital entertainment/business world.We expect six PhD and nine MSc students be trained throughout the 5-year program. These HQPs, together with the technology innovations from our research, will help with maintaining Canada’s lead in the development and deployment of digital and social media services.
在过去的十年中,我们见证了新一代社交、移动的和云计算的快速发展,用于网络多媒体处理和共享。如今,高清视频甚至3D/多视图视频可以通过个人计算设备轻松捕获和浏览,并通过远程云资源方便地处理和存储。用户现在积极参与成为社交生态系统的一部分,而不是被动地接收媒体内容。3G/4G无线网络和智能移动的设备的深入渗透进一步推动了这场革命,这些设备与在线社交网络和媒体共享服务无缝集成。尽管带宽和计算资源日益丰富,但用户生成的媒体内容的数据量不断增加,社交化共享的覆盖范围无限,这对内容和网络服务提供商都提出了前所未有的挑战。高度多样化的媒体内容类型、来源、分发渠道进一步在网络共享系统中的不同组件之间施加复杂的交互。因此,我们提出了以下关键问题:如何能够有效地产生大量的媒体内容,并在大量的客户端与最新的社会,移动的,云计算和通信平台分发?除了可扩展性,能源也成为这些新一代计算和通信平台的关键问题。在移动的终端侧,高度受限的电池库长期以来一直是充电之间的服务时间的瓶颈;在云侧,众所周知,充电中心是耗电的。大量使用CPU、GPU、存储和网络资源的计算和带宽密集型多媒体服务肯定会使情况变得更糟。据预测,多媒体能源消耗每年增长16%,占这些服务年度运营支出的一半。为了实现任何人、任何时间、任何地点的可扩展和节能的媒体共享的最终目标,需要在一个连贯的框架下重新审视和共同优化各个方面的技术进步。在这项拟议的长期研究中,我们将在最新的计算和通信环境中解决上述挑战。我们将不仅关注单个组件的优化,从媒体内容生成,网络和云资源分配,社交媒体传播,到云和本地设备中的节能媒体计算和通信,而且还关注它们之间的交互,这给设计师带来了额外的问题。深入了解这个复杂系统中的模块及其相互作用将有助于在新兴的数字娱乐/商业世界中开发社交媒体,IPTV,电影点播,视频会议和交互式在线游戏等基本服务。我们预计在整个5年计划中将培养6名博士和9名硕士学生。这些HQP,加上我们研究的技术创新,将有助于保持加拿大在数字和社交媒体服务开发和部署方面的领先地位。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Liu, Jiangchuan其他文献

Propagation-based social-aware multimedia content distribution
基于传播的社交感知多媒体内容分发
Fast and Accurate Detection of Unknown Tags for RFID Systems - Hash Collisions are Desirable
快速准确地检测 RFID 系统的未知标签 - 哈希冲突是可取的
  • DOI:
    10.1109/tnet.2019.2957239
  • 发表时间:
    2020-02-01
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Liu, Xiulong;Chen, Sheng;Liu, Jiangchuan
  • 通讯作者:
    Liu, Jiangchuan
WHEN RFID MEETS DEEP LEARNING: EXPLORING COGNITIVE INTELLIGENCE FOR ACTIVITY IDENTIFICATION
  • DOI:
    10.1109/mwc.2019.1800405
  • 发表时间:
    2019-06-01
  • 期刊:
  • 影响因子:
    12.9
  • 作者:
    Fan, Xiaoyi;Wang, Fangxin;Liu, Jiangchuan
  • 通讯作者:
    Liu, Jiangchuan
RoArray: Towards More Robust Indoor Localization Using Sparse Recovery with Commodity WiFi
Lightweight Imitation Learning for Real-Time Cooperative Service Migration
  • DOI:
    10.1109/tmc.2023.3239845
  • 发表时间:
    2024-02-01
  • 期刊:
  • 影响因子:
    7.9
  • 作者:
    Ning, Zhaolong;Chen, Handi;Liu, Jiangchuan
  • 通讯作者:
    Liu, Jiangchuan

Liu, Jiangchuan的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Liu, Jiangchuan', 18)}}的其他基金

Towards Highly Interactive Networked Multimedia Services with Crowd Intelligence
通过群体智能实现高度交互的网络多媒体服务
  • 批准号:
    RGPIN-2019-04040
  • 财政年份:
    2022
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Discovery Grants Program - Individual
Towards Highly Interactive Networked Multimedia Services with Crowd Intelligence
通过群体智能实现高度交互的网络多媒体服务
  • 批准号:
    RGPIN-2019-04040
  • 财政年份:
    2021
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Discovery Grants Program - Individual
Towards Highly Interactive Networked Multimedia Services with Crowd Intelligence
通过群体智能实现高度交互的网络多媒体服务
  • 批准号:
    RGPIN-2019-04040
  • 财政年份:
    2020
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Discovery Grants Program - Individual
Understand the challenges and potentials of serverless computing for realtime networked multimedia
了解实时网络多媒体的无服务器计算的挑战和潜力
  • 批准号:
    543280-2019
  • 财政年份:
    2019
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Engage Grants Program
Towards Highly Interactive Networked Multimedia Services with Crowd Intelligence
通过群体智能实现高度交互的网络多媒体服务
  • 批准号:
    RGPIN-2019-04040
  • 财政年份:
    2019
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Discovery Grants Program - Individual
Scalable and Energy-Efficient Multimedia Content Sharing over New Generation Computing and Communication Platforms
通过新一代计算和通信平台实现可扩展且节能的多媒体内容共享
  • 批准号:
    RGPIN-2014-04765
  • 财政年份:
    2018
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Discovery Grants Program - Individual
Collaborative edge and cloud learning: Potentials and solutions
协作边缘和云学习:潜力和解决方案
  • 批准号:
    522129-2017
  • 财政年份:
    2017
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Engage Grants Program
Scalable and Energy-Efficient Multimedia Content Sharing over New Generation Computing and Communication Platforms
通过新一代计算和通信平台实现可扩展且节能的多媒体内容共享
  • 批准号:
    RGPIN-2014-04765
  • 财政年份:
    2016
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Discovery Grants Program - Individual
Deployment of networking and cloud architectures for intelligent camera network
智能摄像机网络的网络和云架构部署
  • 批准号:
    507132-2016
  • 财政年份:
    2016
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Engage Grants Program
Nomination for NSERC Steacie Memorial Fellowship
NSERC Steacie 纪念奖学金提名
  • 批准号:
    468747-2015
  • 财政年份:
    2016
  • 资助金额:
    $ 3.35万
  • 项目类别:
    EWR Steacie Fellowships - Salary

相似国自然基金

度量测度空间上基于狄氏型和p-energy型的热核理论研究
  • 批准号:
    QN25A010015
  • 批准年份:
    2025
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目

相似海外基金

SBIR Phase I: Scalable Manufacturing Technology for Mobile Signal Penetrating Energy-Efficient Low-Emissivity Windows
SBIR 第一阶段:移动信号穿透节能低发射率窗户的可扩展制造技术
  • 批准号:
    2233675
  • 财政年份:
    2023
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Standard Grant
Flexibly Scalable Energy Efficient Networking (FLEX-SCALE)
灵活可扩展的节能网络 (FLEX-SCALE)
  • 批准号:
    10061981
  • 财政年份:
    2023
  • 资助金额:
    $ 3.35万
  • 项目类别:
    EU-Funded
An Energy-Efficient, CMOS-based, and Scalable Mixed-Signal DNN System with Reconfigurable Crossbars
具有可重新配置交叉开关的节能、基于 CMOS 的可扩展混合信号 DNN 系统
  • 批准号:
    2221753
  • 财政年份:
    2022
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Standard Grant
Collaborative Research: PPoSS: Planning: SEEr: A Scalable, Energy Efficient HPC Environment for AI-Enabled Science
合作研究:PPoSS:规划:SEEr:面向人工智能科学的可扩展、节能的 HPC 环境
  • 批准号:
    2119294
  • 财政年份:
    2021
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Standard Grant
Scalable fabrication of on-chip Li CO2 batteries for efficient electrocatalysts screening and energy storage mechanism study
可扩展制造片上锂二氧化碳电池,用于高效电催化剂筛选和储能机制研究
  • 批准号:
    EP/V002260/1
  • 财政年份:
    2021
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Research Grant
Collaborative Research: PPoSS: Planning: SEEr: A Scalable, Energy Efficient HPC Environment for AI-Enabled Science
合作研究:PPoSS:规划:SEEr:面向人工智能科学的可扩展、节能的 HPC 环境
  • 批准号:
    2119056
  • 财政年份:
    2021
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Standard Grant
Collaborative Research: PPoSS: Planning: SEEr: A Scalable, Energy Efficient HPC Environment for AI-Enabled Science
合作研究:PPoSS:规划:SEEr:面向人工智能科学的可扩展、节能的 HPC 环境
  • 批准号:
    2119203
  • 财政年份:
    2021
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Standard Grant
Integrated scalable quantum receiver for energy efficient data exchange and telecommunication
用于节能数据交换和电信的集成可扩展量子接收器
  • 批准号:
    1927674
  • 财政年份:
    2019
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Standard Grant
CAREER: Scalable Manufacturing of Two-dimensional Atomic Layer Materials for Energy-efficient Electronic Devices via Selective-area Atomic Layer Deposition
职业:通过选择性区域原子层沉积大规模制造用于节能电子设备的二维原子层材料
  • 批准号:
    1751268
  • 财政年份:
    2018
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Standard Grant
Scalable and Energy-Efficient Multimedia Content Sharing over New Generation Computing and Communication Platforms
通过新一代计算和通信平台实现可扩展且节能的多媒体内容共享
  • 批准号:
    RGPIN-2014-04765
  • 财政年份:
    2018
  • 资助金额:
    $ 3.35万
  • 项目类别:
    Discovery Grants Program - Individual
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了